That’s why I have spent the past three years helping to develop an algorithm that uses probabilistic record linkage called “fastLink” that not only makes record linkage across data sets speedy and automated, but also tells the analyst how likely it is that an inexact match of two records is actually correct.

In a recent study co-authored with colleagues Ben Fifield and Kosuke Imai, we apply the algorithm to the question of voter identification. The results raise serious concerns about Georgia’s exact match law — and its likelihood of preventing tens of thousands of valid voters from casting ballots.

Here’s how we did our research

We worked on linking two nationwide voter files from 2014 and 2015 collected by L2 Inc, a national nonpartisan firm that supplies voter data and related technology for campaigns. All active voters in 2014 appeared in the 2015 data set — meaning that we knew a true match always existed. But many records had typographical discrepancies preventing exact matches.

Our analysis found that the “exact match’’ approach would link only 66 percent of voters who were actually the same, correctly identifying about 91 million voters. In other words, “exact matching” would exclude nearly 40 million records that actually did refer to the same voter — disenfranchising quite a few Americans.